Extracting Bounded-level Modules from Deductive RDF Triplestores - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2015

Extracting Bounded-level Modules from Deductive RDF Triplestores

Abstract

We present a novel semantics for extracting bounded-level modules from RDF ontologies and databases augmented with safe inference rules, a la Datalog. Dealing with a recursive rule language poses challenging issues for defining the module semantics, and also makes module extraction algorithmically unsolvable in some cases. Our results include a set of module extraction algorithms compliant with the novel semantics. Experimental results show that the resulting framework is effective in extracting expressive modules from RDF datasets with formal guarantees, whilst controlling their succinctness.
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Dates and versions

lirmm-01086951 , version 1 (15-01-2015)

Identifiers

  • HAL Id : lirmm-01086951 , version 1
  • PRODINRA : 313444

Cite

Marie-Christine Rousset, Federico Ulliana. Extracting Bounded-level Modules from Deductive RDF Triplestores. AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence (AAAI). Austin, USA., Jan 2015, Austin, TX, United States. ⟨lirmm-01086951⟩
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